submit round-28 filter results: MetaX_c-500(5)/Kunlunxin_p-800(4)/hygon_k100-ai(2)/Cambricon_mlu-370-x8(4)/Biren_166m(1), 16 models total

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

main.py

@@ -58,29 +58,34 @@ ACCOUNTS: List[Tuple[str, str, str]] = [
 #  各 GPU 的模型列表（来自 filter_verified_models 脚本的筛选结果）
 # ══════════════════════════════════════════════════════════
 METAX_MODELS = [
-    "AI-ModelScope/stable-diffusion-2-1-base",
-    "AI-ModelScope/t2iadapter_color_sd14v1",
-    "fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
-    "FutureWater/FST-ET1-14B",
-    "okwinds/Rombos-LLM-V2.6-Qwen-14b",
+    "smalltotal/Flux_wx_dust",
+    "fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
+    "kandivault/sprocket-500m",
+    "fpadovani/eng-latn-10mb-100mb_seed10",
+    "ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
 ]
 
 KUNLUNXIN_MODELS = [
-    "fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
+    "fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
+    "kandivault/sprocket-500m",
+    "fpadovani/eng-latn-10mb-100mb_seed10",
+    "ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
 ]
 
 BIREN_MODELS = [
-    "vinayp27/smollm3-medical",
-    "FutureWater/FST-ET1-14B",
-    "okwinds/Rombos-LLM-V2.6-Qwen-14b",
+    "kandivault/sprocket-500m",
 ]
 
 CAMBRICON_MODELS = [
-    "fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
+    "fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
+    "kandivault/sprocket-500m",
+    "fpadovani/eng-latn-10mb-100mb_seed10",
+    "ymh1981/unsloth_qwen2.5_3b_grpo_google_colab_f16",
 ]
 
 HYGON_MODELS = [
-    "fpadovani/dan-latn-10mb-after-ppt-shuff-dyck-10mb-ckpt500_seed3407",
+    "fpadovani/eng-latn-10mb-after-ppt-Dp-10mb-ckpt500_seed10",
+    "fpadovani/eng-latn-10mb-100mb_seed10",
 ]
 
 MTHREADS_MODELS = [
@@ -650,10 +655,10 @@ PPU_MODELS = [
     "espressovi/BODHI-qwen-3-maze-8b-distil",
 ]
 
-# 本轮提交第二十六轮过滤结果：MetaX_c-500(5) / Kunlunxin_p-800(1) / hygon_k100-ai(1) /
-# Cambricon_mlu-370-x8(1) / Biren_166m(3)，共11个；沿用多账号 fallback 轮转。
-# 产出为历轮最低：候选池与上轮基本相同，而上轮筛出的84个已在 v1.0.32 全部提交成功并
-# 产生验证记录被排除；需灌入这些卡未跑过的新模型才会有新产出。
+# 本轮提交第二十八轮过滤结果：MetaX_c-500(5) / Kunlunxin_p-800(4) / hygon_k100-ai(2) /
+# Cambricon_mlu-370-x8(4) / Biren_166m(1)，共16个；沿用多账号 fallback 轮转。
+# 候选池已回升到6053个（上轮仅3046），但产出仍只有16个，说明新加入的模型大多
+# 在这几张卡上已跑过；需灌入这些卡未跑过的新模型才会有更多产出。
 # 本轮不提交 Mthreads_s4000（保留既有列表）/ ppu_zw_810e（机制B无白名单权限）/
 # Sunrise_pt-200-x1（v1.0.13已完成）/
 # Iluvatar_bi-150（本轮筛选为0；且本仓库 framework=vllm，现有 iluvatar 镜像均为 llamacpp/GGUF，缺 vllm 版镜像）